One solution for reducing traffic congestion on highways is to make existing highways more efficient through automation. To be safe and effective, however, automated highways require means for positioning vehicles within lanes as well as maintaining optimum distance between vehicles. Therefore, fully automated highway systems require sensor and data processing systems to detect and control the separation of moving vehicles.
Positioning vehicles on an automated highway, such as the proposed Intelligent Vehicle Highway System (IVHS), is complicated by the clutter of unwanted information from the environment that is continually received by any sensor system. Provisions must be made for system calibration, changing weather, vehicles entering and exiting the highway, and numerous other obstacles that might be encountered. Various systems have been proposed for automated highways, including those employing passive systems such as stereo vision for measuring distance between vehicles and active sensors such as mm wave radar, laser radar, and sonar. The presently known mid available systems, however, have high cost factors and/or technical problems that have not been overcome. In particular, any radar system to be applied to automobile intelligent cruise control (AICC) must have a low manufacturing cost to be commercially acceptable. Given these constraints and the desire to develop automated highways, there is a need for safe, effective, low cost, real time systems for sensing and controlling the separation of automotive vehicles on the highways.